Analysis of Functional MRI Data using Clustering Algorithm

Ramesh Babu N

ISBN 10: 3659687731 / ISBN 13: 9783659687730

Published by LAP LAMBERT Academic Publishing, 2016

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - The utilization of contextual information was studied for the analysis of fMRI data. The approach consisted of two phases: computation of a statistical parametric map and activation detection by contextual clustering. The iterative clustering algorithm presented in this work is based on Besag's ICM algorithm. Our contribution has been to apply and evaluate the ICM in the context of hypothesis testing and statistical parametric maps. The results indicate that the power of the developed contextual algorithm is superior to that of conventional voxel-by-voxel thresholding of a statistical parametric map. Although fMRI data were used to test the algorithm, the construction of the algorithm is general and it can be used to detect objects with unknown distribution from a known background distribution in other similar problems as well.

Seller Inventory # 9783659687730

Bibliographic Details

• Title: Analysis of Functional MRI Data using Clustering Algorithm
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2016
• Language: English
• ISBN 10: 3659687731
• ISBN 13: 9783659687730
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 119 grams

About this title

Synopsis

The utilization of contextual information was studied for the analysis of fMRI data. The approach consisted of two phases: computation of a statistical parametric map and activation detection by contextual clustering. The iterative clustering algorithm presented in this work is based on Besag’s ICM algorithm. Our contribution has been to apply and evaluate the ICM in the context of hypothesis testing and statistical parametric maps. The results indicate that the power of the developed contextual algorithm is superior to that of conventional voxel-by-voxel thresholding of a statistical parametric map. Although fMRI data were used to test the algorithm, the construction of the algorithm is general and it can be used to detect objects with unknown distribution from a known background distribution in other similar problems as well.

About the Author

He received his Masters degree from Anna University, India and obtained his Ph.D degree from VIT University, India.He has around 15 years of teaching experience with around 8 years of research experience. Presently he is working as a Head, Department of Instrumentation, School of Electrical Engineering, VIT University, Vellore, India.